########################################################################### # Copyright 2019 (C) Hui Lan # Written permission must be obtained from the author for commercial uses. ########################################################################### # Purpose: dictionary & pickle as a simple means of database. # Task: incorporate the functions into wordfreqCMD.py such that it will also show cumulative frequency. import os import pickle from datetime import datetime def lst2dict(lst, d): ''' Store the information in list lst to dictionary d. Note: nothing is returned. ''' for x in lst: word = x[0] freq = x[1] if not word in d: d[word] = freq else: d[word] += freq def dict2lst(d): return list(d.items()) # a list of (key, value) pairs def merge_frequency(lst1, lst2): d = {} lst2dict(lst1, d) lst2dict(lst2, d) return d def load_record(pickle_fname): f = open(pickle_fname, 'rb') d = pickle.load(f) f.close() return d def save_frequency_to_pickle(d, pickle_fname): f = open(pickle_fname, 'wb') #exclusion_lst = ['one', 'no', 'has', 'had', 'do', 'that', 'have', 'by', 'not', 'but', 'we', 'this', 'my', 'him', 'so', 'or', 'as', 'are', 'it', 'from', 'with', 'be', 'can', 'for', 'an', 'if', 'who', 'whom', 'whose', 'which', 'the', 'to', 'a', 'of', 'and', 'you', 'i', 'he', 'she', 'they', 'me', 'was', 'were', 'is', 'in', 'at', 'on', 'their', 'his', 'her', 's', 'said', 'all', 'did', 'been', 'w'] exclusion_lst = [] d2 = {} for k in d: if not k in exclusion_lst and not k.isnumeric() and len(k) > 1: d2[k] = d[k] pickle.dump(d2, f) f.close() def unfamiliar(path,word): if not os.path.exists(path): return None with open(path,"rb") as f: dic = pickle.load(f) dic[word] += [datetime.now().strftime('%Y%m%d%H%M')] with open(path,"wb") as fp: pickle.dump(dic,fp) def familiar(path,word): f = open(path,"rb") dic = pickle.load(f) if len(dic[word])>1: del dic[word][0] else: dic.pop(word) fp = open(path,"wb") pickle.dump(dic,fp) if __name__ == '__main__': lst1 = [('apple',2), ('banana',1)] d = {} lst2dict(lst1, d) # d will change save_frequency_to_pickle(d, 'frequency.p') # frequency.p is our database lst2 = [('banana',2), ('orange', 4)] d = load_record('frequency.p') lst1 = dict2lst(d) d = merge_frequency(lst2, lst1) print(d)